Ensemble Platform for Species Distribution Modeling
BinaryTransformation
BIOMOD_CrossValidation
Project ensemble species distribution models onto new environment
Create and evaluate an ensemble set of models and predictions
Format input data, and select pseudo-absences if wanted, for usage in ...
Load species distribution models built with biomod2
Run a range of species distribution models
BIOMOD_ModelingOptions
BIOMOD_PresenceOnly
Project a range of calibrated species distribution models onto new env...
Analyze the range size differences between projections of species dist...
BIOMOD_Tuning
BIOMOD_EnsembleModeling() output object class
BIOMOD_FormatingData() output object class (with pseudo-absences)
BIOMOD_FormatingData() output object class
bm_ModelingOptions output object class
BIOMOD_Modeling() output object class
bm_ModelingOptions output object class
bm_ModelingOptions output object class
BIOMOD_Projection() output object class
BIOMOD_Modeling and BIOMOD_EnsembleModelingoutput object class
Ensemble model output object class (when running `BIOMOD_EnsembleModel...
Single model output object class (when running BIOMOD_Modeling())
Deprecated functions in package biomod2.
Convert probability values into binary values using a predefined thres...
Build cross-validation table
Calculate the best score according to a given evaluation method
Standardized formula maker
Configure the modeling options for each selected model
Plot boxplot of evaluation scores
Plot mean evaluation scores
Plot species range change
Plot response curves
Plot boxplot of variables importance
Select pseudo-absences
Loop to compute all single species distribution models
Sample binary vector
Sample all levels of a factorial variable
Surface Range Envelope
Tune models parameters
Variables' importance calculation
calculate.stat
Check duplicated cells
Transform categorical into numeric variables
Get categorical variable names
Get class of environmental data provided
Load library for GAM models
Transform predictions data.frame from long to wide with models as colu...
.transform.outputs.list
Find.Optim.Stat
getStatOptimValue
Functions to extract informations from biomod2_model objects
Functions to extract informations from BIOMOD.models.out, `BIOMOD.pr...
Functions to load BIOMOD.stored.data objects
makeFormula
models_scores_graph
plot method for BIOMOD.formated.data object class
Functions to get predictions from biomod2_model objects
Functions to get predictions from biomod2_ensemble_model objects
Functions to get predictions from biomod2_model objects
Functions to get predictions from biomod2_ensemble_model objects
ProbDensFunc
Check whether SpatRaster is an empty rast()
response.plot2
sample.factor.levels
sre
summary method for BIOMOD.formated.data object class
variables_importance
Dummy function to clean working directory after package checks
Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization. The package permits to run consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) dataset and to combine them in ensemble models and ensemble projections. Some bench of other evaluation and visualization tools are also available within the package.